Grasping Benchmarks: Normalizing for Object Size \& Approximating Hand Workspaces
This addresses a standardization problem for researchers in robotic grasping, though it is incremental as it builds on existing concepts without introducing new paradigms.
The paper tackles the lack of standardized measurements for robotic hand size and object graspability by proposing a functional measurement procedure based on generic grasping scenarios, demonstrating it on seven hand configurations to enable quantitative communication and workspace approximation.
The varied landscape of robotic hand designs makes it difficult to set a standard for how to measure hand size and to communicate the size of objects it can grasp. Defining consistent workspace measurements would greatly assist scientific communication in robotic grasping research because it would allow researchers to 1) quantitatively communicate an object's relative size to a hand's and 2) approximate a functional subspace of a hand's kinematic workspace in a human-readable way. The goal of this paper is to specify a measurement procedure that quantitatively captures a hand's workspace size for both a precision and power grasp. This measurement procedure uses a {\em functional} approach -- based on a generic grasping scenario of a hypothetical object -- in order to make the procedure as generalizable and repeatable as possible, regardless of the actual hand design. This functional approach lets the measurer choose the exact finger configurations and contact points that satisfy the generic grasping scenario, while ensuring that the measurements are {\em functionally} comparable. We demonstrate these functional measurements on seven hand configurations. Additional hand measurements and instructions are provided in a GitHub Repository.